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FIX: Fix HyperGeometric.logcdf support bounds and safe indexing - #8493
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- Align lower bound to max(0, n - bad) and upper bound to min(good, n) - Return -inf when value < lower and 0.0 when value >= upper - Clamp summation indexing with safe_value to prevent out-of-support evaluations - Add test_hypergeometric_logcdf_bounds covering boundary edge cases
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Hi @pymc-devs! 👋 This PR is ready for review. It addresses the support bound discrepancies in HyperGeometric.logcdf when Please let me know if any adjustments, additional tests, or documentation changes are needed. I'm very happy to address any feedback! Thank you for your time and guidance. |
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Closes #8492
Description
This PR fixes mathematical boundary handling and numerical instability in
HyperGeometric.logcdf.Context & Problem
Previously,
HyperGeometric.logcdfevaluated bounds using fixed heuristics (value < 0andvalue < n):logsumexp, evaluatingbetalnon non-positive integers rather than immediately returning-inf.logsumexprather than immediately returning0.0.# TODO: Use lower upper in locgdf for smarter logsumexp?.Changes Made
lower = pt.switch(pt.gt(n - bad, 0), n - bad, 0)andupper = pt.switch(pt.lt(good, n), good, n), matchingHyperGeometric.logp.safe_valueto ensurept.arangenever executes over out-of-support points.-infwhenvalue < lowerand0.0whenvalue >= upper.test_hypergeometric_logcdf_boundsintests/distributions/test_discrete.pychecking lower-tail, upper-tail, and intermediate points againstscipy.stats.hypergeom.# TODOcomment.Checklist